Data-throughput enhancement using data mining-informed cognitive radio

Khashayar Kotobi, Philip B. Mainwaring, Conrad S. Tucker, Sven G. Bilén

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

We propose the data mining-informed cognitive radio, which uses non-traditional data sources and data-mining techniques for decision making and improving the performance of a wireless network. To date, the application of information other than wireless channel data in cognitive radios has not been significantly studied. We use a novel dataset (Twitter traffic) as an indicator of network load in a wireless channel. Using this dataset, we present and test a series of predictive algorithms that show an improvement in wireless channel utilization over traditional collision-detection algorithms. Our results demonstrate the viability of using these novel datasets to inform and create more efficient cognitive radio networks.

Original languageEnglish (US)
Pages (from-to)221-238
Number of pages18
JournalElectronics
Volume4
Issue number2
DOIs
StatePublished - Mar 26 2015

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Hardware and Architecture
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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